This invention relates to both a method and apparatus, as illustrated in FIG. 1, for the non-invasive determination of blood oxygen, particularly in a fetus.
Oxygen is essential to human life; for the adult, child and fetus. Asphyxia is the condition where the lack of oxygen causes the cessation of life. Hypoxia is a deficiency in the amount of oxygen reaching the tissues. While hypoxia is not fatal it may cause severe neurological damage.
The first manifestation of fetal hypoxia is a decrease in oxygen content and an accumulation of carbon dioxide in the blood. The latter, in turn, causes a decrease in the pH values of the blood resulting in respiratory acidosis. In the second stage there is an additional build up of organic acids due to anaerobic glycolysis. In the third stage the acidosis, which has progressed in the meantime and which is predominantly of metabolic character, begins to have a negative effect on the neurological health of the fetus. The central nervous system becomes depressed and irreversible changes can occur depending upon the duration of the hypoxic condition. This, in turn, can result in brain damage and/or cerebral palsy.
Methods currently available to the obstetrician and labor room staff for assessment of fetal status include non-invasive measures such as monitoring the contraction patterns of the expectant mother and monitoring fetal heart rate (either through the abdominal wall of the expectant mother or, after the cervix is minimally dilated, via an electrode placed in the scalp or buttocks of the fetus). In the presence of possible fetal distress suggested by clinical evaluation, or non-invasive monitoring methods, or invasive procedures such as intermittent fetal scalp blood samples (for fetal blood pH determination), or percutaneous umbilical blood sampling (PUBS), emergent caesarean section is often performed.
With both the non-invasive or invasive measures for determining fetal status identified above, information concerning the most important physiological parameter of fetal well-being, blood oxygen saturation, is not available to the physician. Changes in fetal heart rate and blood pH are secondary manifestations of a primary condition, fetal hypoxia. The measurement of a secondary manifestation such as fetal heart rate would be adequate, provided that changes in fetal heart rate were predictably correlated with blood oxygen saturation. Unfortunately, research has shown that this correlation is not present. See Monbeit et al., "Fetal Heart Rate and Transcutaneous Monitoring During Experimentally Induced Hypoxia in the Fetal Dog," Pediatric Research 1988, Vol. 23, No. 6, p. 548; Blocking et al., "Effects of Reduced Uterine Blood Flow on Accelerations and Decelerations in the Heart Rate of Fetal Sheep", Am. J. Obstetrics and Gynecology 1986, 154 pp. 329-335; and Myers et al., "Predictability of the State of Fetal Oxygenation for Quantitative Analysis of the Components of Late Decelerations", Am J Obstetrics Gynecology 1973, 115 p. 1083.
In addition to the foregoing, controversies about fetal heart monitoring have existed since it was first introduced into clinical practice in 1968. Recently fetal heart monitoring has come under additional criticism because researchers have found that its use does not improve survival rate or neurological health. Additionally, the enormous rise in operative deliveries (primarily Caesarean sections) for fetal distress as the result of the introduction of continuous fetal monitoring is the major objection of some authors against the general application of this technique. The false positive indication of fetal distress in cases where actually no complication emerges is the major shortcoming of fetal heart monitoring when used as the only technique of supervision. See, Paper, "Benefits and Detriments of Fetal Heart Monitoring". Seminars in Perinatology, 1978, 2 p. 113.
The complementary use of a biochemical parameter with fetal heart monitoring has been proposed as an adequate solution to the foregoing concerns. To some extent fetal blood analysis is a reliable method to identify intrauterine complications. However, this technique has several disadvantages. First, the cervix must be at least 3 centimeters dilated, the fetus must be a vertex (head down) presentation, and the head must be well applied to the cervix. Second, it only provides intermittent information about the biochemical status of the fetus, and in some cases has to be repeated at short intervals if fetal heart rate patterns remain or appear pathological. Third, obtaining a fetal blood sample is difficult and it is virtually impossible to tell if it is venous blood, which contains mostly deoxygenated hemoglobin (Hb) (i.e., low O.sub.2 saturation) or arterial blood which contains mostly oxygenated hemoglobin (HbO.sub.2) (i.e., high O.sub.2 saturation). This uncertainty results in the pH of the fetal blood being the actual perimeter measured rather than oxygen saturation. A pH decrease is an accurate measurement of hypoxia, but is often manifested too late as the condition of hypoxia must exist for quite some time. Another problem is that the sample could be that of the mother, not the fetus. Finally, a traumatization of the fetal skin is inevitable and infection may occur, as one or more incisions have to be made in order to take blood samples. Thus, this procedure is complicated with problems of inaccuracies and the potential hazards of invasive procedures and, therefore, not widely utilized. See "Methodology and Clinical Value of Transcutaneous Blood Gas Measurements in the Fetus", Intrapartum Biochemical Monitoring of the Fetus, 1987, p. 94.
Another invasive method to assess fetal status, but only on a one time basis, is by percutaneous umbilical blood sampling (PUBS). This is done by locating the umbilical cord with ultrasound guidance and, using a long needle, piercing through the abdominal wall, through the uterine wall and into the umbilical cord to obtain arterial and/or venous blood. This procedure is dangerous, requires considerable expertise and cannot be used to continuously monitor fetal well-being during labor.
The ability to determine blood oxygen saturation in both pediatric ( including newborn) and adult populations via oximetry, particularly pulse oximetry, is well known. Oximetry in such applications (but not in fetal monitoring, as explained below) is an accepted method of oxygen determination and has been utilized in clinical medicine for approximately 10 years. Basically, the oximeter provides, either non-invasively or invasively, a continuous way of determining blood oxygen saturation to assess the need for adjusting the supply of oxygen to the patient or for assessing the effect of therapies. It is essentially used to ensure that the patient's oxygen level is adequate to prevent damage to organs such as the brain, heart, lungs, and kidneys.
There are two types of oximeters: (1) invasive oximeters; and (2) non-invasive pulse oximeters. The invasive oximeters must have the light beam and detector optics in contact with blood. Thus, the light that is emitted from the instrument interacts only with blood and is then recorded by the detector. In clinical medicine the sampling device, typically a fiber optic catheter probe, is placed in a large blood vessel in the body and measurement is made on the blood that passes by the catheter. The invasive oximeters can be problematic if the catheter is abutting the wall of the blood vessel. In this circumstance the measuring probe is partially sampling the wall of a blood vessel and no accurate determination of blood saturation is made. Non-invasive (i.e., pulse) oximeters do not require direct contact with the blood. The light emitted from a pulse oximeter interacts with skin, fat, muscle, bone and blood before it is detected. The non-invasive pulse oximeters are able to remove the interferences generated by the bone, etc. by performing a ratio of or determining the difference between data from high and low pulse pressures generated by the heart of the individual being monitored. As only arterial blood pulses, non-invasive oximeters only analyze arterial blood which is pulsating, thus the name pulse oximeter. The specific method by which a pulse oximeter removes the interferences generated by skin, etc. is explained below.
An understanding of the present status of oximetry and why it is not reliable for fetal monitoring can be obtained by analyzing the state of the art which, for convenience, can be divided into: (1) existing patented technology; (2), technology published in current literature; and (3) the published attempted use of existing technology for fetal oximetry.
The prior patented technology can be broken down into three categories:
1) Non-invasive blood oxygen saturation determination instruments utilizing a transmission sampling technique, with analysis based on two wavelengths: U.S. Pat. Nos. 4,859,056, 4,846,183, 4,824,242, 4,807630, 4,807,630, 4,807,631, 4,800,885, 4,781,195, 4,714,341, 4,603,700, 4,586,513, 3,847,483 and 3,638,640. U.S. Pat. Nos. 4,770,179, 4,700,708, 4,653,498 and 4,621,643 to New et al. are believed to represent the best examples of this technology and are assigned to Nellcor, Inc., a leading manufacturer of pulse oximeters. PA1 2) Invasive blood oxygen saturation determination instruments utilizing a fiber optic probe with reflectance sampling in which the probe must be inserted into a blood containing area: U.S. Pat. Nos. 4,830,488, 4,813,421, 4,807,632, 4,697,593, 4,651,741, 4,623,248, and 4,523,279. U.S. Pat. No. 4,114,604 to Shaw et al. is believed to represent the best example of this prior art. The Abbott Critical Care Oximetrix 3 instrument is believed to be based on this patent. PA1 3) Non-invasive blood oxygen saturation determination utilizing a reflectance method with analysis of the reflected light by a linear algorithm employing only two wavelengths. This technology is represented by U.S. Pat. No. 4,859,057 to Taylor et al. PA1 a. Irradiating a biological fluid (i.e., blood) having unknown values of a known characteristic (i.e., glucose) with infrared energy having a least several wavelengths so that there is differential absorption of at least some of the wavelengths by the biological fluid as a function of both the wavelengths and the known characteristic. The differential absorption causes intensity variations of the wavelengths incident from the biological fluid, as a function of the wavelengths and the unknown values. PA1 b. Measuring the intensity variations from the biological fluid. PA1 c. Calculating the unknown values of the known characteristic (i.e., glucose) in the biological fluid from the measured intensity variations utilizing a multivariate algorithm and a mathematical calibration model. The algorithm includes all independent sources of intensity variations v. wavelengths information obtained from irradiating a set of samples in which the values of the known characteristic are known. The algorithm also includes more wavelengths than samples in the set of samples. The model is constructed from the set of samples and is a function of the known values of the characteristic and the intensity variations vs. wavelengths information obtained from irradiating the set of samples. PA1 a. A source of infrared energy having at least several wavelengths. PA1 b. Apparatus for coupling the source of the infrared energy to the biological fluid to enable the biological fluid to differentially absorb at least some of the wavelengths. The differential absorption causes intensity variations of the infrared energy incident from the biological fluid as a function of the several wavelengths and of the unknown value of the known characteristics. PA1 c. Apparatus for measuring the intensity variations. PA1 d. A computer including: PA1 a. Accommodation of nonlinear spectral responses without an explicit mathematical model for the response and without a degradation in prediction accuracy; PA1 b. Compensation for the presence of interferences of undetermined origin (e.g., chemical contaminants or physiological variations ); and PA1 c. Identification of spurious or outlier samples in both the calibration samples and in the unknown samples. PA1 a. Simultaneous and rapid sampling at multiple frequencies. Rapid sampling is necessary due to the rapid rate of the fetal heart and large variations in beat-to-beat pulse pressure. To distinguish the true maximum and minimum of the vascular system, a sampling rate .gtoreq.50 Hz would be desirable, and is feasible using our technology. PA1 b. Use of an emitter/detector apparatus, in connection with fiber optics, which is well-suited for attachment to the fetus for reflection sampling. Traditional transmission oximeters are not useful due to the virtual impossibility of obtaining data by transmission sampling through the fetus during delivery, which requires that the detector and source be separated physically. The reflectance apparatus of Taylor is larger and requires a constant pressure application due to two discrete light sources. Constant pressure application would be extremely difficult to implement during fetal delivery. PA1 c. Analysis of the spectral information with a multivariate algorithm. A multivariate analysis will be superior to either univariate or bivariate analyses because the information available at multiple frequencies can be combined to yield more information with a higher precision and reliability than the information available at one or several discrete frequencies or ratios. The preferred algorithms are known as partial least squares (PLS) and principle component regression (PCR). These algorithms are particularly well-suited for this application due to: their ability to model or approximate most nonlinearities; well-developed outlier detection methods; and ability to create a mathematical model of the spectral information using a minimal number of factors. Other suitable algorithms are classic least squares (CLS), Q-matrix method, cross correlation, Kalman filtering and multiple linear regression (MLR). MLR is sometimes referred to as inverse least squares (ILS). PA1 d. Providing the doctor with a measure of validity or an assurance of accuracy by employing outlier detection methods. The ability to identify false negatives is extremely important because the consequences of hypoxia on the fetus can result in death or life-long neurological deficits. On the other hand, the ability to eliminate false positives will reduce the incidence of unnecessary caesarean sections, a surgical intervention with risks for both fetus and mother.
The methods disclosed in the above-identified patents on pulse oximetry (e.g. New et al. and Taylor et al.) are based upon several related facts. First, the concentration of blood in a given location of the body varies with each pulse of the heart. With each heart beat a systolic pulse pressure is generated which leads to a maximal expansion (i.e. dilation) of the vascular system. During the resting period of the cardiac cycle (i.e., diastole) there is no pressure generated and the vascular system returns to a minimal size. This variation can be measured with optically based methods, by introducing a light source near the skin and detecting either the reflected or the transmitted light intensity. The light transmitted or reflected during diastole (i.e., the period when the arterial system is at its minimal size) interacts with the skin, fat, bone, muscle and blood. Light transmitted or reflected during systole, (i.e., the period of maximum expansion of the arterial system) interacts with the same skin, fat, bone, muscle, and blood, plus an additional amount of blood which is present due to the expansion of the arterial system. If the diastolic signal is subtracted from the systolic signal the result is a signal which represents the additional amount of blood. The subtraction process removes the interferences created by the interaction of the light with the skin, fat, bone and muscle. The quality and clarity of the subtraction generated signal is related to the amount of additional blood present which, in turn, is proportional to the pulse pressure, (i.e., the difference between systolic pressure and diastolic pressure). See FIG. 2 for a graphical representation of the above process. Note that invasive oximeters do not perform any type of pulse related subtraction because the light interacts with blood only and no removal of other interferences is necessary.
All present pulse instruments assess variations in red blood cell concentration by utilizing a light frequency near or at the isobestic point, where measurement of pulsatile volume is made independent of oxygen saturation. An isobestic wavelength is one which does not change intensity with oxygen saturation but only with blood concentration. Consequently, such a wavelength (typically in the range of 800-1000 nm) intentionally eliminates information on oxygen saturation and establishes a reference. A second wavelength in the red portion of the spectrum, which is sensitive to oxygen saturation, is detected by either a transmission or reflection sampling technique. By using the isobestic wavelength as a reference and by comparing its spectral intensity to the intensity of the second wavelength in the red portion of the spectrum, it is possible to determine the oxygen saturation of the blood non-invasively.
Oximeters based on invasive procedures also use a frequency at or near the isobestic point. In invasive instruments the intensity at the isobestic frequency is related to the amount of light returning or reflected by the sample which, in turn, is related to the hematocrit (i.e., the percent volume of the blood volume occupied by red blood cells). Basically, invasive methods simply take a ratio of the "red" wavelength divided by the isobestic wavelength.
An additional similarity among existing oximeters, both invasive and non-invasive, is the irradiation of the tissue or blood with only one wavelength at a given time. In U.S. Pat. No. 4,653,498 to New et al. and U.S. Pat. No. 4,859,057 to Taylor et al. the respective inventions utilize a red light source and an infrared light source which are energized at different instants in time. In the patents to Shaw et al., U.S. Pat. Nos. 3,847,483 and 4,114,604, light-emitting diodes corresponding to 3 separate wavelengths are energized at a set percentage of the operating cycle, in a non-overlapping relationship by a repetitive pulse generator. Thus, the instruments disclosed in all prior patents of which we are aware are limited by their inability to obtain information at a variety of wavelengths simultaneously due to the fact that a single detector element is used. Additionally, the sampling rate is limited by the time necessary for the light source at a given wavelength to obtain an appropriate brightness and stability.
In all prior known applications, the algorithm (i.e., a procedure for solving a given type of mathematical problem) used for analysis of the two, or sometimes three, wavelengths detected have typically utilized a single analysis frequency with a single background correction frequency to determine a single proportionality constant describing the relationship between absorbance and concentration (i.e., univariate or one variable algorithms). In the patents to New et al. the blood oxygen saturation determination is made by utilizing a ratio between the ambient transmission and the change in transmission occurring during each pulse at both wavelengths. The remainder of the univariate algorithm consists of a manipulation of this ratio in conjunction with several constants for saturation determination (see columns 13-15 of U.S. Pat. No. 4,653,498). The net result is that New et al. describe a multi-parameter but univariate method utilizing two wavelengths for oxygen saturation determination.
The invasive apparatus described by Shaw, et al., U.S. Pat. No. 3,847,483, uses an optical catheter for determination of oxygen saturation in a blood vessel or other blood filled container. The apparatus uses two wavelengths of light which originate from two light-emitting diodes, which are alternately energized for about 25% of the operating cycle in a non-overlapping manner. The oxygen saturation is then determined by an equation, which may be characterized as a nonlinear, bivariate algorithm, employing 6 calibration constants. A subsequent U.S. Pat. No. 4,114,604, also to Shaw, et al., discloses what is described in the Abstract as an "improved catheter oximeter [which] operates on radiation at three or more different wavelengths applied to and scattered back from blood under test to provide an indication of oxygen saturation and is considerably less sensitive to accuracy-degrading variations in the blood and its environment and in the oximeter measuring system." The actual saturation determination is made by using 2 ratios calculated from light intensity measurements at 3 wavelengths. The following nonlinear, two variable equation is used for the calculation: ##EQU1## where A.sub.0, A.sub.1, A.sub.2, B.sub.0, B.sub.1, and B.sub.2, are experimentally derived constants, and I.sub.0, I.sub.1, and I.sub.2 correspond to measured intensities at 3 different wavelengths. Shaw et al. state that: "Since the relationship between oxygen saturation and the ratio of light intensities is not quite linear, the apparatus of the present invention uses piecewise linear relationships or nonlinear relationships to measure oxygen saturation, over a wide dynamic range of valves" (column 2, line 50-54). The authors further state that the "oxygen saturation measured in accordance with Equation 3 [above] is a function of the ratios of light intensity measurements which is useful for determining oxygen saturation over a narrow (emphasis added) range of valves. However, to compensate for the nonlinearities of the underlying phenomena which have significant effect over a wide dynamic range of valves, Equation 3 can be augmented by adding terms proportional to the square of a ratio of light intensities, as indicated in [Equation 4] shown below." (See column 3, lines 20-29). ##EQU2##
Thus, Shaw et al. recognize the nonlinear characteristics involved in oxygen saturation determination and recommend a possible method for overcoming this problem. It is important to note that the Shaw methodology utilizes only a few discrete non-overlapping frequencies taken at different non-overlapping time periods. It is also important to note that it is not suited to non-invasive determinations as it does not disclose any method of eliminating background components such as hair, bone and skin. This is because Shaw, et al. place their detector directly in the blood. Also, because of the extreme difficulty in inserting a catheter in the blood vessel of a newborn, let alone the essentially closed environment of a fetus, invasive procedures are not usable.
The reflectance oximeter disclosed by Taylor et al., U.S. Pat. No. 4,859,057, does not disclose as specific mathematical relationship between the two wavelengths utilized. The scope of the patent is summarized in the following: "In a further method in accordance with the invention for reflectance oximetry wherein energized and reflected light from said sources is sensed to produce red and infrared reflectance signals respectively, the method comprising separating the a.c. and d.c. components of said reflectance signals, determining the difference between the maximum and minimum valves of each pulse of said a.c. component and determining oxygen saturation from said difference by comparison of said difference with a look up table." See column 4, lines 56-66. The d.c. component corresponds to the sum or average amount of light reflected back from the tissue. The a.c. component is generated by the pulsating blood. Although the terminology is different, the net result is that Taylor, et al. subtract the minimum from the maximum components of the a.c. signal, which is the same as subtracting the systolic and diastolic signals. Again, the technology employs only two wavelengths of light, with the intensity from each wavelength being recorded at different and discrete times.
An additional methodology associated with invasive reflectance determination is disclosed by Hoeft et al., "In Vivo Measurement of Blood Oxygen Saturation by Analysis of Whole Blood Reflectance Spectra", SPIE Vol 1067 Optical Filters in Medicine IV (1989). The actual instrumentation utilized consists of an optical multichannel instrument with a grating that separates light into different wave lengths and a CCD detector array. Like other investigators, they employ a simple relationship based upon one of the two wavelength regions used being an isobestic range, (i.e., a wavelength range at which little or no difference appears in the optical reflectance of oxyhemoglobin vs. reduced hemoglobin). Oxygen saturation is then assumed to be a linear function of the ratio of the light intensity reflected from the blood at the isobestic and non-isobestic wavelengths as follows: EQU O.sub.2 Saturation=A +B(I.sub.1 /I.sub.2)
where I.sub.1 is light intensity diffusely scattered back from the blood at the isobestic wavelength, I.sub.2 is the light intensity diffusely back scattered at the non-isobestic wavelength, and A and B are experimentally determined calibration coefficients. The method of Hoeft et al., differs from the other above identified methodologies in that they allow for simultaneous sampling of multiple frequencies and by summing the total light intensity from 600 to 840 nm and equating it to I.sub.2. I.sub.1 was found by summing the isobestic wavelengths from 840-850 nm. Thus, there is no overlap between I.sub.1 and I.sub.2. Additionally, the coefficients A & B are determined using a 2nd order polynomial in hemoglobin concentration. Before the O.sub.2 saturation of an unknown sample can be determined, the hemoglobin of the blood sample must be known for the calculation of coefficients A & B. Although Hoeft's methodology utilizes information from more than one frequency, it uses a univariate algorithm, because only one variable results from each frequency range summation (i.e., a single number). Additionally, Hoeft's method is not suited to non-invasive analysis since it requires a determination of hemoglobin concentration via wet chemistry, for subsequent determination of coefficients A and B.
Over the past few years significant research has been done in the attempt to create a clinically useful pulse oximeter for fetal monitoring, but none have been reliable or accurate enough to reach clinical (i.e., standard/non-experimental) medicine. The reason for this failure is multi-factorial, including the difficulty of the environment and the parameters under which a fetal pulse oximeter must operate. This work has focused on modifying existing pulse oximeters for reflectance measurement.
The work by Johnson "Monitoring the Fetus with a Pulse Oximeter", First International Symposium on Intrapartum Surveillance, October 1990, and Gardosi "Intrapartum O.sub.2 Saturation Trend and Acidosis", October 1990, First International Symposium on Intrapartum Surveillance have shown that the normal fetus at time of delivery has a blood oxygen saturation of approximately 60% or 75%, depending upon which investigators' results are accurate. A possible reason for this discrepancy is, as discussed below, that existing pulse (non-invasive) oximeters are inaccurate at low oxygen saturations. The work of Chapman et al., "Range of Accuracy of Two Wavelength Oximetry" Chest, Vol. 89, No. 4 April, 1986, pp. 540-542, and Severinghaus et al., "Accuracy of Response of Six Pulse Oximeters to Profound Hypoxia", Anesthesiology, Vol. 67, No. 4, Oct. 1987, pp. 551-558, have demonstrated that existing pulse oximeters are not accurate at O.sub.2 saturations below 75%. Thus, the modification of existing pulse oximeters for fetal monitoring is destined for failure, because the fetus is at a saturation of less than 75%, and existing pulse oximeters do not work well below 75%.
While the inability of existing pulse oximeters to work in the fetal oxygen saturation range may seem to be an obvious oversight, there are several reasons that have inhibited development of an accurate and reliable fetal monitor. The main reasons existing oximeter technology is not suitable for fetal monitoring are: (1) the requirement that the sampling measurement be made by reflectance spectroscopy; (2) fetal circulation has a much lower pulse pressure than that of adults; (3) the critical range for making a decision on operative intervention will be in the 30% to 60% oxygen saturation region; and (4) fetal heart rate is approximately twice that of the average adult.
A comparison between transmission sampling employed by present pulse oximeters, the type used by Chapman et al. and Severinghaus et al., versus the reflectance sampling required by the environment when monitoring the fetus, reveals that it is difficult to obtain spectral data from the fetus with signal-to-noise ratios comparable to data presently obtained by oximeters from adults or newborns. In comparison to transmission measurements, the use of reflectance spectroscopy decreases the magnitude of the return signal by approximately a factor of 10. Any decrease in the amount of signal is damaging to the prediction, because of the resultant decrease in the signal-to-noise ratio. As the signal-to-noise ratio decreases, the precision of the oxygen saturation determination decreases.
A requirement of non-invasive arterial blood oxygen saturation determination is that the background components of hair, skin and bone be removed. To remove such background components, existing non-invasive oximeters use the difference between diastole and systole signals to obtain a "blood" signal that is analyzed for saturation determination. Thus, the larger the difference between systolic and diastolic, (i.e., the larger the pulse pressure differential) the larger the blood volume analyzed, and the higher the signal-to-noise ratio. While the fetus is in utero, fetal circulation is present which results in similar right and left heart pressures; specifically systolic pressures of 75-80 mm Hg and diastolic pressures of 50-55 mm Hg. Thus, the difference between diastole and systole is significantly less, approximately 20 mm Hg, in comparison to 60 mm Hg pulse pressure in the average adult. This fact has not gone unnoticed as demonstrated by Siker's statement that, "Standard monitors need larger wave-forms than the fetal scalp may generate during labor", "Reflection Pulse Oximetry in Fetal Lambs", First International Symposium on Intrapartum Surveillance, October, 1990. As stated by Johnson, supra, "good readings were only obtained in 25% of cases . . . ". While applicants cannot be sure of what is meant by "readings", it is strongly suspected that Johnson is referring to the signal resulting from comparison of the systolic and diastolic signals. Thus, physiological parameters present in the fetus, such as low pulse pressure and the necessity for reflectance sampling, result in decreased signal-to-noise ratios which degrade the accuracy and precision of prediction.
The environment under which the fetal pulse oximeter is required to operate is further complicated by the low oxygen saturations it is required to determine. The work of Chapman et al. and Severinghaus et al. have demonstrated that the accuracy of oxygen saturation determination becomes quite poor at saturations of less than 75%. Although not mentioned or discussed by either Chapman et al. or Severinghaus et al., the source of this error is the nonlinear relationship between oxygen saturation and reflected or transmitted light intensity, as discussed below. If one uses the oxygen saturation errors reported by Chapman et al. and Severinghaus et al. for extrapolation to fetal monitoring, their reported errors should be considered as a best case situation due to the fact that their data were obtained from adults by transmission sampling (in contrast to reflectance sampling required for a fetal pulse oximeter). Their reported fetal oximetry errors are in excess of 10% absolute error. See data from Johnson and Dassel et al. Thus, using the reported data acquired by existing technology, the oxygen saturation of the fetus cannot be determined with an error of less than 10% for the expected fetal oxygen saturations below 75%. Based upon the work of Gardosi the fetus starts to develop metabolic acidosis secondary to decreased oxygen supply at an oxygen saturation of approximately 60%. Thus, if the present technology were used in a clinical situation for monitoring a fetus during labor, an oximeter reading of 60% oxygen saturation might actually be 70%, in which case no operative intervention should be initiated. Alternatively, the saturation might actually be 50% in which case some type of operative intervention may be considered. The clinical usefulness of current oximeters for fetal applications, with a best case average error of determination of approximately 10% oxygen saturation, is questionable.
An additional problem associated with the existing technology is that the two or more wavelengths of light used for the determination of the oxygen saturation are not sampled at the same time. The process of switching between wavelengths can be done rapidly but there is a finite amount of time required for obtaining the required intensities at each wavelength. The time necessary for each data value is determined by the time required for the light emitting diode (LED) to reach a stable intensity and for the detector to record the received intensity value. Both time constraints are strongly influenced by the capacitance of the oximeter system. The lack of simultaneous frequency sampling is of less consequence in the adult population in which the normal heart rate is approximately 80 beats per minute, and beat-to-beat variation in pulse pressure, caused by respiration, is quite small. In the fetus the average heart rate is between 120 and 160 beats per minute, and large variations in beat-to-beat pulse pressure are present due to uterine contractions. Because existing technology is unable to simultaneously record multiple frequencies, the same blood volume is not sampled. In the adult a given frequency could be measured at a given pulse with a second measurement occurring at the next pulse. If a similar methodology is used on the fetus, the spectral intensity values corresponding to the additional blood present are likely to correspond to different amounts of additional blood due to the variation in pulse pressure. These resulting intensity values could be used to generate a spectrum, but the spectrum would lead to imprecise analyses since the variation of the amount of blood present in sequential pulses would cause corresponding variations in the intensities at each frequency.
In summary, the physiological and physical parameters associated with fetal monitoring represent an extreme environment under which existing oximeter technology cannot operate with reasonable, clinically acceptable accuracy. While the articles presented at the First International Symposium on Intrapartum Surveillance are not prior to applicants' invention, they are cited to illustrate the continued shortcomings of existing fetal monitoring.
It is essential to realize that all prior art oximeters, both pulse and invasive, have used 3 or less measured intensities and/or two or less variables for analysis. Both New et al. and Shaw et al. use a limited number of wavelengths, but use nonlinear univariate or bivariate algorithms. No algorithm is specified in Taylor. Methods that simultaneously use two or more variables are known as multivariate methods. As used in this application, multivariate will refer to simultaneous analysis of three or more variables. Not only do multivariate statistical methods provide enhanced analysis of component concentrations, but such multivariate methods have also recently made possible the estimation of physical and chemical properties of materials from their spectra. Such multivariate statistical methods have been used in the analysis of salt water, peas, glucose and thin film dielectrics.
A simple illustration of the increased capability of multivariate methods in component concentration determination is provided by FIGS. 3A., 3B. and 3C. In FIG. 3A. one can see that an impurity component, whose spectrum overlaps that of the analyte, can affect the spectrum of the analytic band and, therefore, the accuracy of the analysis will suffer when the analysis is performed at a single wavelength .nu..sub.1 or when ratioing .nu..sub.1 to a reference wavelength. The measured absorbance, A.sub.m, at the analysis wavelength, .nu..sub.1, for a sample containing the impurity is different than the true absorbance, A.sub.t, of the analyte at that wavelength. If the calibration curve in FIG. 3.B. is from spectra of samples containing no impurity, then the presence of the impurity in the sample will yield an apparent concentration that may be quite different from the true concentration. This error will remain undetected if the intensity was measured at only one wavelength. If the impurity is included in the calibration samples but varies randomly in concentration in the samples, a calibration plot similar to that in FIG. 3.B. will exhibit large scatter among the data, and the result will be both a poor calibration curve and concentration estimates that have poor precision for the unknown samples. However, with analysis at more than one wavelength, not only can the presence of the impurity be detected, FIG. 3.C., but if its presence is included in the calibration, quantitative analysis of the analyte is possible with multivariate calibration methods, even if the impurity and its concentration are unknown.
An indication that the unknown is different from the set of calibration samples not containing the impurity is obtained by plotting the absorbance of the calibration samples and the unknown sample spectra at two frequencies selected for analysis. As exhibited in FIG. 3.C., the spectrum of the sample containing the impurity (indicated by "x") is obviously different than that of the calibration spectra (i.e. it is an outlier). Outliers are those samples or spectra among either the calibration or unknown data which do not exhibit the characteristic relationship between composition and spectra of the other calibration samples. The sensitivity in detecting outliers is increased by increasing the number of frequencies included in the analysis. The number of independently varying impurities that can be accounted for in the analysis is also increased by increasing the number of frequencies utilized.
Accurate univariate methods are dependent upon the ability to identify a unique, isolated band for each analyte. Multivariate methods can be used even when there is overlap of spectral information from various components over all measured spectral regions. Unlike univariate methods, multivariate techniques can achieve increased precision from redundant information in the spectra, can account for base-line variations, can more fully model nonlinearities, and can provide outlier detection.
The general approach that is used when statistical multivariate methods are applied to quantitative spectroscopy problems requires calibration in which a mathematical model of the spectra is generated. See FIG. 4. This calibration model can then be used for prediction of concentrations in unknown samples. The spectra of a series of calibration standards are first obtained, such that the spectra span the range of variation of all factors which can influence the spectra of future unknown samples. Assuming that the calibration uses samples that contain all the components expected in the unknown samples and spans their expected range of variation, the calibration will be able to empirically account for (or at least approximate) non-ideal behavior in Beer's law, independent of the source of the non-ideal behavior. Nonlinearities may arise from spectroscopic instrumentation, dispersion, or intermolecular interactions. As used in this application "nonlinear" refers to any deviation in Beer's law or the inverse Beer's law relationship (i.e., which cannot be modeled with the standard linear expression y=mx+b; where y represents the dependent variable, x is the independent variable, and m and b are, respectively, the slope and intercept). As was noted by Shaw et al., the spectral response with changing oxygen saturation is not linear.
Once the empirical calibration relating spectra and component concentrations has been performed, then the spectrum of the unknown sample can be analyzed by a multivariate prediction step to estimate the component concentration or properties. If the calibration samples are truly representative of the unknown sample, then the result of the analysis will be an estimate which will have a precision similar to that found in the set of calibration samples. In addition, spectral residuals (i.e., the difference between measured and estimated spectra) can be used to determine if the unknown sample is similar to the calibration samples. If the unknown sample is not representative of the calibration samples (i.e., is an outlier) spectroscopic interpretation of the residuals can often be made to determine the source of any differences between unknown and calibration samples. See Haaland, David M.: "Multivariate Calibration Methods Applied to Quantitative FT-IR Analysis" in Practical Fourier Transform Infrared Spectroscopy, Industrial and Laboratory Chemical Analysis, Edited by J. R. Ferraro and K. Krishman, Academic Press, Inc. 1990.
The multivariate methods which are best suited for analysis of oximeter data are those that model the spectra using an inverse Beer's law model, such as principal component regression (PCR) or partial least squares (PLS). In an inverse Beer's law model the concentration of each component in the mixture is represented as a linear function of the sampled absorbance spectrum. An advantage of this multivariate approach is that the nonlinearities in the spectral response to changes in composition can be accommodated without the need for an explicit model. For the chemical components to be predicted, PCR or PLS analysis is used to construct a linearly independent set of factors based upon a set of calibration spectra (i.e., spectra for which the composition to be predicted is known). The number of these component factors which are useful for prediction (the "rank" of the model) is selected by a cross-validation procedure, which is also used to estimate the precision of subsequent predictions. PLS and PCR methods are capable of achieving accurate and precise results in the presence of linear and nonlinear dependencies in the absorbance spectrum at various frequencies. Thus, an entire spectral region can be used in multivariate analysis without the need for the spectroscopist to choose an optimal set of wavelengths for the analysis. Similarly, these methods of computation are not sensitive to linear dependencies introduced by over sampling of information at many frequencies in the construction of the calibration samples. See Cahn, et al., "Multivariate Calibration of Infrared Spectra for Quantitative Analysis Using Designed Experiments". Applied Spectroscopy 1988 Vol. 42 No. 5 p. 865.
U.S. Pat. No. 4,975,581 to Robinson et al. discloses a method and apparatus for, particularly, quantitatively determining the amount of glucose in a human. The method relates to determining one or more unknown concentration values of a known characteristic (e.g. glucose) via the steps of:
The method can be used in vivo and non-invasively, in vivo and invasively, and in vitro.
The apparatus disclosed in U.S. Pat. No. 4,975,581 includes:
i. A stored model constructed from a set of samples in which the values of the known characteristic are known. The model is a function of the known values from the set of samples and intensity v. wavelength information obtained from the set of samples. PA2 ii. An algorithm including (a) all independent sources of intensity variations v. wavelengths information from both the set of samples and the biological fluid and (b) more wavelengths than samples. The algorithm utilizes the model for calculating the unknown value of the known characteristic of the biological fluid from the measured intensity variations from the biological fluid.
The applicants recognize that the preferred embodiment of U.S. Pat. No. 4,975,581 utilizes the partial least squares algorithm. However, the reasons for utilizing the PLS algorithm in the present invention are quite different from the reasons it was utilized to determine glucose concentrations. The limiting factor in the determination of a blood analyte, such as glucose, is the lack of information available. For example, when a diabetic develops a high or low blood sugar condition they do not turn another color. This lack of visible change is in stark contrast to the profound visual changes observed when someone becomes hypoxic. The person turns blue. The determination of a blood analyte requires a very high signal-to-noise ratio and a sophisticated algorithm for extraction of a minuscule amount of information (glucose is, normally, 0.1 weight percent of blood). In the case of a pulse oximeter suitable for fetal monitoring, the information is abundant (i.e., babies that are profoundly hypoxic are blue), but the environment of operation is extreme. As has been previously mentioned and will later be emphasized, the reflected light-oxygen saturation relationship is highly nonlinear, the signal for analysis is extremely noisy and the present invention must remove the interfering background components by correlating with the pulsating blood. Also the frequency regions used for analysis are separate (primarily visible as opposed to primarily infrared and near infrared) and the basic instrumentation is different (i.e., a Fourier transform infrared spectrometer is used for glucose determination, versus a dispersive spectrometer used in the present invention).
Despite past and continuing failures, an accurate assessment of fetal oxygen saturation can be obtained by measuring the peripheral blood oxygen saturation in the fetus. The technology for the realization of this goal, no more invasive than the electronic heart monitors currently used, is disclosed herein. This improved method and apparatus should lead to a reduction in the rate of Cesarean sections for apparent fetal distress and the total elimination of the invasive technique of fetal blood sampling. In this way a fetus born in the best possible condition will result, while operative intervention is kept to the necessary minimum. Further, such a monitor could serve to improve the survival rate of otherwise compromised fetuses by early and accurate detection of real problems. Thus, the ultimate goal of a healthy mother and baby will be enhanced.
It is an object of the present invention to provide a fetal oximeter which can easily and accurately operate in the extreme environment of fetal monitoring, thus overcoming the shortcomings of existing technology.
The object of the pulse oximeter of the present invention is to overcome the limitations of prior art oximeters, including their inability to obtain information at a variety of wavelengths simultaneously, and the limitation inherent in the time necessary for the intermittently energized light sources in such prior art oximeters to reach the required brightness and stability.
In contrast to Shaw et al., another object of the present invention is to utilize multiple frequencies with simultaneous sampling, employ an algorithm which can model nonlinearities over the entire clinically observed blood oxygen saturation range and which is suitable for non-invasive measurements in the fetus' environment.
It is another and important object to determine if a sample's spectrum and subsequently determined oxygen value (from either the calibration set or the fetus) is representative of the calibration samples. This is crucial for the implementation of an accurate and reliable clinical instrument. Identifying and removing outlier samples from the calibration set will drastically improve the accuracy and precision of the analysis. Identification of outliers among the unknown samples provides information for evaluating the validity of the fetal blood oxygen saturation determination. This ability is especially important in this medical application because the consequences of hypoxia on the fetus can result in death or lifelong disability. For example, use of technology not applying outlier detection methods to a spurious spectral sample would generate an oxygen saturation value, but the resulting value could not be trusted to be accurate. Generation of a spurious spectrum could result from instrument malfunction, improper attachment of the monitor to the fetus or the chorioamniotic membrane of the mother, or some unusual physiological variation in the fetus such as sickle cell disease. If such an unreliable result was used to make a clinical decision, the fetus could suffer. According to the present invention, utilization of a pulse oximeter employing outlier detection methods would result in the generation of a "flag" when analyzing a spurious sample, indicating that the analysis was unreliable. No clinical decision would be based upon possible false information and the mother and fetus would not suffer harm.
It is another object of the invention to provide an oximeter based on a multivariate inverse Beer's law model, such as PLS or PCR, to provide the following benefits:
No simple or obvious combination of the prior art will result in an instrument capable of non-invasively and accurately monitoring fetal oxygen saturation over wide ranges of saturation values. For instance, existing oximeters do not measure multiple wavelengths simultaneously. Therefore, the full advantages of using a powerful multivariate algorithm like PLS could not be obtained due to the limited number of frequencies available when using existing instrumentation. Though Taylor, et al., discloses reflectance sampling, all known commercially available pulse oximeters use transmission sampling. Further, conventional oximeters do not use gratings or any mechanism that separates light into its constituent wavelengths.
The present invention represents a significant advancement in apparatus and methodology by: